• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.372-379
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• 2017

Software reliability factor during the software development process is elementary. Case of the infinite failure NHPP for identifying software failure, the occurrence rates per fault (hazard function) have the characteristic point that is constant, increases and decreases. In this paper, we propose a reliability model using the chi - square distribution which depends on the degree of freedom that represents the application efficiency of software reliability. Algorithm to estimate the parameters used to the maximum likelihood estimator and bisection method, a model selection based on the mean square error (MSE) and coefficient of determination($R^2$), for the sake of the efficient model, were employed. For the reliability model using the proposed degree of freedom of the chi - square distribution, the failure analysis using the actual failure interval data was applied. Fault data analysis is compared with the intensity function using the degree of freedom of the chi - square distribution. For the insurance about the reliability of a data, the Laplace trend test was employed. In this study, the chi-square distribution model depends on the degree of freedom, is also efficient about reliability because have the coefficient of determination is 90% or more, in the ground of the basic model, can used as a applied model. From this paper, the software development designer must be applied life distribution by the applied basic knowledge of the software to confirm failure modes which may be applied.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.43-50
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• 1996

This paper is concerned with assessing goodness of fit of gravity models. The Chi-square test, or one of its asymptotic equivalents, is usually recommended for the purpose. A difficulty that frequently arises, particularly when working with urban travel data, is that the expected number of trips for most origin-destination(O-D) pairs are small. In order to test goodness of fit of gravity model, a simple approach, which depends on the number of O-D pairs and certain trip totals being large, is proposed in this paper. In addition, derivation of variance of Chi-square ratio is proposed to test the confidence interval of Chi-square ratio and application of its results with simulated data set is made to verify the usefulness of the results.

• Genomics & Informatics
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• v.5 no.4
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• pp.168-173
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• 2007

In previous nuclear genomic association studies, Random Forests (RF), one of several up-to-date machine learning methods, has been used successfully to generate evidence of association of genetic polymorphisms with diseases or other phenotypes. Compared with traditional statistical analytic methods, such as chi-square tests or logistic regression models, the RF method has advantages in handling large numbers of predictor variables and examining gene-gene interactions without a specific model. Here, we applied the RF method to find the association between mitochondrial single nucleotide polymorphisms (mtSNPs) and diabetes risk. The results from a chi-square test validated the usage of RF for association studies using mtDNA. Indexes of important variables such as the Gini index and mean decrease in accuracy index performed well compared with chi-square tests in favor of finding mtSNPs associated with a real disease example, type 2 diabetes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.5-9
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• 2001

In this paper, we propose the new audio watermarking method and can be used on line processing. Instead of the wavelet transform, we use the integer wavelet transform for the reduction of the computational load. The watermark associated with the chi-square distribution is inserted into the signal on the integer wavelet domain. When extracting the watermark, the spread spectrum methods are used with the coefficients associated with the covariance sequence. We show that the chi-square distribution is a good tool for the spread spectrum method on the wavelet domain. This watermarking technique may be used for the control of the electrical product which can be controlled with the hidden signals and can be moved according to the audible signals simultaneously.

• International Journal of Reliability and Applications
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• v.4 no.3
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• pp.97-111
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• 2003

By applying Theorem 2.6.4 (Fang and Zhang, 1990, p.66) the dispersion matrix of a multivariate power exponential (MPE) distribution is derived. It is shown that the MPE and the gamma distributions are related and thus the MPE and chi-square distributions are related. By extending Fang and Xu's Theorem (1987) from the normal distribution to the Univariate Power Exponential (UPE) distribution an explicit expression is derived for calculating the probability of an UPE random variable over an interval. A representation of the characteristic function (c.f.) for an UPE distribution is given. Based on the MPE distribution the probability density functions of the generalized non-central chi-square, the generalized non-central t, and the generalized non-central F distributions are derived.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.644-660
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• 2016

The real-time detection of malware remains an open issue, since most of the existing approaches for malware categorization focus on improving the accuracy rather than the detection time. Therefore, finding a proper balance between these two characteristics is very important, especially for such sensitive systems. In this paper, we present a fast portable executable (PE) malware detection system, which is based on the analysis of the set of Application Programming Interfaces (APIs) called by a program and some technical PE features (TPFs). We used an efficient feature selection method, which first selects the most relevant APIs and TPFs using the chi-square ($KHI^2$) measure, and then the Phi (${\varphi}$) coefficient was used to classify the features in different subsets, based on their relevance. We evaluated our method using different classifiers trained on different combinations of feature subsets. We obtained very satisfying results with more than 98% accuracy. Our system is adequate for real-time detection since it is able to categorize a file (Malware or Benign) in 0.09 seconds.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.1-7
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• 1994

Using a Monte-Carlo simulation technique we evaluate the empiricla distribution of a pseudo-chi-square statistic based on symmetrically Winsorized sum of squares when the population is normally distributed, and search for a chi-square distribution with appropriate degrees of freedom which can be referred to an approximate distribution for Winsorized chi-square.

• Tunnel and Underground Space
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• v.21 no.1
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• pp.50-65
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• 2011

Analysis of correlation and behavior characteristics at elastic wave velocity have studied on Korean rock data after checking population size and Chi-square method. Behavior characteristics are quite different from each rock and mechanical parameters at elastic wave velocity. This study shows it is necessary to analize correlation to rock behavior characteristics for correct answer from natural rock.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.785-787
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• 2008

생명체의 생명현상을 주관하는 각종 화학반응들은 단백질이 관여하고 있다. 단백질은 일정한 질서에 따라 서로 조립되기도 하고, 기능적으로 연관돼 네트워크를 이루고 있다. 이 네트워크를 구성하는 단백질-단백질 상호작용은 단백질의 기능과 밀접하게 관련되어 있다. 즉, 상호작용하는 단백질은 같은 기능을 수행할 가능성이 크다. 이러한 사실은 단백질-단백질 상호작용을 통해 기능이 알려지지 않은 미지 단백질의 기능을 예측할 수 있게 한다. 대표적인 연구로는 이웃 노드에 존재하는 기능분포를 이용하는 이웃노드 카운트(Neighborhood Counting)방식과 특정 기능의 나타날 빈도를 계산하여 기능을 예측하는 카이-제곱(Chi-Square)방식 등이 있다. 본 논문에서는 단백질 기능 예측의 정확성을 높이기 위해 이들 두 방식의 장점을 취합한 보완된 카이-제곱 방식을 제안한다. 그리고 다양한 단백질 상호작용 네트워크 데이터를 비교 분석하여 보완된 카이-제곱 방식이 기능 예측의 정확성이 높음을 증명한다.

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.